Using CloudSat and the A-Train to Estimate Tropical Cyclone Intensity in the Western North Pacific

Abstract

CloudSat joined the A-Train constellation in June 2006 to enhance the understanding of the global heat budget by providing measurements of cloud properties on a global scale, and provide the first statistics on the vertical structure of clouds from space. The data collected by CloudSat could provide forecasters a tool in estimating tropical cyclone (TC) intensity in areas where in situ measurements are scarce. This thesis expanded the data set and methodology employed by Luo et al. (2008) to estimate the maximum sustained winds using satellite based cloud-top slope estimates. The method requires an eye or near-eye overpass as well as simultaneous and accurate measurements of cloud-top height, cloud-top temperature, and cloud profiling information across the center of a storm. A primary objective of this thesis was to examine sensitivities of estimated maximum wind to the overpass distance to the TC center, the TC intensity, and TC structure asymmetries due to vertical wind shear. A significant dependency was identified to the distance between the satellite overpass and TC center. In general, there was an over-estimation of weaker storms and an under-estimation of strong storms. The greatest accuracy is found where the satellite overpass was relatively near the TC center.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2014
Accession Number
ADA620536

Entities

People

  • Jeffrey K. Seibold

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Artificial Satellites
  • Data Sets
  • Detectors
  • Earth Sciences
  • Heat Energy
  • Intensity
  • Jet Propulsion
  • Latent Heat
  • Measurement
  • Meteorology
  • Surface Temperature
  • Tropical Cyclones
  • United States
  • Wind
  • Wind Shear

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Atmospheric Science/Meteorology
  • Computational Modeling and Simulation

Technology Areas

  • Space
  • Space - Satellites